An Extensive Evaluation of Read Trimming Effects on Illumina NGS Data Analysis

By Cristian Del Fabbro, Simone Scalabrin, Michele Morgante, Federico Manuel Giorgi. PLoS ONE, 2013

434 citations recorded by the source corpus.

Next Generation Sequencing is having an extremely strong impact in biological and medical research and diagnostics, with applications ranging from gene expression quantification to genotyping and genome reconstruction. Sequencing data is often provided as raw reads which are processed prior to analysis 1 of the most used preprocessing procedures is read trimming, which aims at removing low quality portions while preserving the longest high quality part of a NGS read. In the current work, we evaluate nine different trimming algorithms in four datasets and three common NGS-based applications (RNA-Seq, SNP calling and genome assembly). Trimming is shown to increase the quality and reliability of the analysis, with concurrent gains in terms of execution time and computational resources needed.

Subfields: Artificial Intelligence, Molecular Biology

View Paper: https://www.semanticscholar.org/paper/56102c419e3f4b921d25c1b76866f03019604457

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Artificial Intelligence

1. Rong Lei
2. P. S. Ward
3. Shou-Wei Ding
4. Hongshan Jiang
5. Shuifang Zhu
6. Yufei Huang

In Molecular Biology

1. P. S. Ward
2. M. Branstetter
3. J. Longino
4. Rong Lei
5. Yidong Chen
6. Zhiliang Lu
7. Lin Zhang
8. Hui Liu

Citations in the corpus

• A protocol for RNA methylation differential analysis with MeRIP-Seq data and exomePeak R/Bioconductor package. (2014, background): “Please refer to [33] for a comprehensive review.”
• Enriching the ant tree of life: enhanced UCE bait set for genome‐scale phylogenetics of ants and other Hymenoptera (2017, methodology): “Using the FASTQ files, we cleaned and trimmed raw reads using ILLUMIPROCESSOR (Faircloth 2013), which is a wrapper around TRIMMOMATIC (Lohse et al. 2012; Del Fabbro et al. 2013), and we assembled reads de novo using a wrapper (phyluce_assembly_assemblo_trinity) around TRINITY v2013-02-25 (Grabherr e”
• Skewer: a fast and accurate adapter trimmer for next-generation sequencing paired-end reads (2014, background): “However, in real applications, quality trimming, which is outside of the scope of this paper, has been reported to improve the mapping rate and facilitate downstream data analysis [22].”